Citation
Chua, Sook Ling and Marsland, Stephen and Guesgen, Hans W. (2016) A supervised learning approach for behaviour recognition in smart homes. Journal of Ambient Intelligence and Smart Environments, 8 (3). pp. 259-271. ISSN 1876-1364 Full text not available from this repository.Abstract
One application of Ambient Intelligence (AmI) that supports people in their daily activities is the smart home, which has become a popular topic for research over the past 10 years. The smart home can support the inhabitant in a variety of ways, such as watching for potential risks, detecting any abnormality, adapting the home for environmental conditions and inducing behavioural change. This often requires the smart home to recognise the behaviours of the inhabitant. In this paper, we introduce a method that can accurately recognise the inhabitant’s behaviours. This includes both the segmentation of the sensor stream and the identification of behaviours. We demonstrate our algorithm on sensor data from real smart homes.
Item Type: | Article |
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Uncontrolled Keywords: | Behaviour recognition, activity segmentation, hidden Markov model, smart home |
Subjects: | H Social Sciences > H1-99 Social Sciences (General) |
Divisions: | Faculty of Computing and Informatics (FCI) |
Depositing User: | Ms Rosnani Abd Wahab |
Date Deposited: | 15 Nov 2017 17:55 |
Last Modified: | 21 Dec 2022 05:55 |
URII: | http://shdl.mmu.edu.my/id/eprint/6474 |
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